Model predictive control of a mimo system
Model Predictive Control (MPC) is a control method that deals with the multivariable system with constraints. In this dissertation, the MPC methodology is demonstrated on the Coupled Tank System. Using the first principle method, the system parameters for the Coupled Tank System are determined. M...
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sg-ntu-dr.10356-695192023-07-04T15:03:20Z Model predictive control of a mimo system Chipurapalli Raj Shekhar Ling Keck Voon School of Electrical and Electronic Engineering DRNTU::Engineering::Electrical and electronic engineering Model Predictive Control (MPC) is a control method that deals with the multivariable system with constraints. In this dissertation, the MPC methodology is demonstrated on the Coupled Tank System. Using the first principle method, the system parameters for the Coupled Tank System are determined. Model Validation is carried out by comparing simulated data of the model developed with the actual plant. Augmented state space model with incremental input is developed which is used to ensure offset free tracking of the set point. The appropriate choice of augmented state space model is important for the controller performance. Further, the coupled tank system is interfaced with NI DAQmx 6221E using the LabVIEW software. Many experiments has been carried out for the tuning of MPC parameters, control horizon (Nc), prediction horizon (Np) and control weighing factor (λ). The correct selection of MPC parameters are made for implementing MPC algorithm on the coupled tank system. One of the most important features of MPC method is the system constraints. Experiments are carried out when the slew rate constraints, input constraints and output constraints are applied. Comparison between MPC with constraints and MPC without constraints is done. Master of Science (Computer Control and Automation) 2017-02-01T09:12:11Z 2017-02-01T09:12:11Z 2017 Thesis http://hdl.handle.net/10356/69519 en 113 p. application/pdf |
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DRNTU::Engineering::Electrical and electronic engineering Chipurapalli Raj Shekhar Model predictive control of a mimo system |
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Model Predictive Control (MPC) is a control method that deals with the multivariable system
with constraints. In this dissertation, the MPC methodology is demonstrated on the Coupled
Tank System. Using the first principle method, the system parameters for the Coupled Tank
System are determined. Model Validation is carried out by comparing simulated data of the
model developed with the actual plant.
Augmented state space model with incremental input is developed which is used to ensure offset
free tracking of the set point. The appropriate choice of augmented state space model is
important for the controller performance.
Further, the coupled tank system is interfaced with NI DAQmx 6221E using the LabVIEW
software. Many experiments has been carried out for the tuning of MPC parameters, control
horizon (Nc), prediction horizon (Np) and control weighing factor (λ). The correct selection of
MPC parameters are made for implementing MPC algorithm on the coupled tank system.
One of the most important features of MPC method is the system constraints. Experiments are
carried out when the slew rate constraints, input constraints and output constraints are applied.
Comparison between MPC with constraints and MPC without constraints is done. |
author2 |
Ling Keck Voon |
author_facet |
Ling Keck Voon Chipurapalli Raj Shekhar |
format |
Theses and Dissertations |
author |
Chipurapalli Raj Shekhar |
author_sort |
Chipurapalli Raj Shekhar |
title |
Model predictive control of a mimo system |
title_short |
Model predictive control of a mimo system |
title_full |
Model predictive control of a mimo system |
title_fullStr |
Model predictive control of a mimo system |
title_full_unstemmed |
Model predictive control of a mimo system |
title_sort |
model predictive control of a mimo system |
publishDate |
2017 |
url |
http://hdl.handle.net/10356/69519 |
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1772826209772634112 |